Michael I. Jordan

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Michael Jordan
Michael Irwin Jordan

(1956-02-25) February 25, 1956 (age 68)
Alma materUniversity of California, San Diego
Known forLatent Dirichlet allocation
Awards WLA Prize (2022)
Scientific career
InstitutionsUniversity of California, Berkeley
University of California, San Diego
Massachusetts Institute of Technology
ThesisThe Learning of Representations for Sequential Performance (1985)
Doctoral advisorDavid Rumelhart
Donald Norman
Doctoral students
Other notable students

Michael Irwin Jordan ForMemRS[6] (born February 25, 1956) is an American scientist, professor at the University of California, Berkeley, research scientist at the Inria Paris, and researcher in machine learning, statistics, and artificial intelligence.[7][8][9]

Jordan was elected a member of the National Academy of Engineering in 2010 for contributions to the foundations and applications of machine learning.

He is one of the leading figures in machine learning, and in 2016 Science reported him as the world's most influential computer scientist.[10][11][12][13][14][15]

In 2022, Jordan won the inaugural World Laureates Association Prize in Computer Science or Mathematics, "for fundamental contributions to the foundations of machine learning and its application."[16][17][18]


Jordan received his BS magna cum laude in Psychology in 1978 from the Louisiana State University, his MS in Mathematics in 1980 from Arizona State University and his PhD in Cognitive Science in 1985 from the University of California, San Diego.[19] At the University of California, San Diego, Jordan was a student of David Rumelhart and a member of the Parallel Distributed Processing (PDP) Group in the 1980s.

Career and research[edit]

Jordan is the Pehong Chen Distinguished Professor at the University of California, Berkeley, where his appointment is split across EECS and Statistics. He was a professor at the Department of Brain and Cognitive Sciences at MIT from 1988 to 1998.[19]

In the 1980s Jordan started developing recurrent neural networks as a cognitive model. In recent years, his work is less driven from a cognitive perspective and more from the background of traditional statistics.

Jordan popularised Bayesian networks in the machine learning community and is known for pointing out links between machine learning and statistics. He was also prominent in the formalisation of variational methods for approximate inference[1] and the popularisation of the expectation–maximization algorithm[20] in machine learning.

Resignation from Machine Learning[edit]

In 2001, Jordan and others resigned from the editorial board of the journal Machine Learning. In a public letter, they argued for less restrictive access and pledged support for a new open access journal, the Journal of Machine Learning Research, which was created by Leslie Kaelbling to support the evolution of the field of machine learning.[21]

Honors and awards[edit]

Jordan has received numerous awards, including a best student paper award[22] (with X. Nguyen and M. Wainwright) at the International Conference on Machine Learning (ICML 2004), a best paper award (with R. Jacobs) at the American Control Conference (ACC 1991), the ACM-AAAI Allen Newell Award, the IEEE Neural Networks Pioneer Award, and an NSF Presidential Young Investigator Award. In 2002 he was named an AAAI Fellow "for significant contributions to reasoning under uncertainty, machine learning, and human motor control."[23] In 2004 he was named an IMS Fellow "for contributions to graphical models and machine learning."[24] In 2005 he was named an IEEE Fellow "for contributions to probabilistic graphical models and neural information processing systems."[25] In 2007 he was named an ASA Fellow.[26] In 2010 he was named a Cognitive Science Society Fellow[19][27] and named an ACM Fellow "for contributions to the theory and application of machine learning."[28] In 2012 he was named a SIAM Fellow "for contributions to machine learning, in particular variational approaches to statistical inference."[29] In 2014 he was named an International Society for Bayesian Analysis Fellow "for his outstanding research contributions at the interface of statistics, computer sciences and probability, for his leading role in promoting Bayesian methods in machine learning, engineering and other fields, and for his extensive service to ISBA in many roles."[30]

Jordan is a member of the National Academy of Sciences, a member of the National Academy of Engineering and a member of the American Academy of Arts and Sciences.[citation needed]

He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He received the David E. Rumelhart Prize in 2015 and the ACM/AAAI Allen Newell Award in 2009. He also won the 2020 IEEE John von Neumann Medal.

In 2016, Jordan was identified as the "most influential computer scientist", based on an analysis of the published literature by the Semantic Scholar project.[31]

In 2019, Jordan argued that the artificial intelligence revolution hasn't happened yet and that the AI revolution required a blending of computer science with statistics.[32]

In 2022, Jordan was awarded the inaugural World Laureates Association Prize by non-governmental and non-profit international organization World Laureates Association, for fundamental contributions to the foundations of machine learning and its application.[33][34]


  1. ^ a b Zeliadt, N. (2013). "Profile of Michael I. Jordan". Proceedings of the National Academy of Sciences. 110 (4): 1141–1143. Bibcode:2013PNAS..110.1141Z. doi:10.1073/pnas.1222664110. PMC 3557047. PMID 23341554.
  2. ^ Bio highlights of Prof. MI Jordan
  3. ^ "Professor Michael Jordan wins 2020 IEEE John von Neumann Medal". 6 December 2019.
  4. ^ Michael I. Jordan at the Mathematics Genealogy Project Edit this at Wikidata
  5. ^ Jordan, Michael Irwin (1985). The Learning of Representations for Sequential Performance. ProQuest 303340092 – via ProQuest.
  6. ^ "Royal Society elects outstanding new Fellows and Foreign Members". The Royal Society. 6 May 2021. Retrieved 13 November 2022.
  7. ^ Jacobs, R. A.; Jordan, M. I.; Nowlan, S. J.; Hinton, G. E. (1991). "Adaptive Mixtures of Local Experts". Neural Computation. 3 (1): 79–87. doi:10.1162/neco.1991.3.1.79. PMID 31141872. S2CID 572361.
  8. ^ David M. Blei, Andrew Y. Ng, Michael I. Jordan. Latent Dirichlet allocation. The Journal of Machine Learning Research, Volume 3, 3/1/2003
  9. ^ Michael I. Jordan, ed. Learning in Graphical Models. Proceedings of the NATO Advanced Study Institute, Ettore Maiorana Centre, Erice, Italy, September 27-October 7, 1996
  10. ^ "Who's the Michael Jordan of computer science? New tool ranks researchers' influence". Science | AAAS. 2016-04-19. Retrieved 2018-03-28.
  11. ^ "Top 50 authors in computer science" (PDF). Science.
  12. ^ "Who is the Michael Jordan of computer science?". Berkeley Engineering. 2016-11-01. Retrieved 2018-03-28.
  13. ^ Austria, IST. "IST Austria: Lecture by Michael I. Jordan available on IST Austria's YouTube channel". ist.ac.at. Retrieved 2018-03-28.
  14. ^ "Who's the Michael Jordan of Computer Science? New Tool Ranks Researchers' Influence | Careers | Communications of the ACM". cacm.acm.org. Retrieved 2018-03-28.
  15. ^ "Michael I. Jordan". awards.acm.org. Retrieved 2018-03-28.
  16. ^ "Winners of the Inaugural WLA Prize Announced, RMB 10 Million for Each Prize - News - WLA Prize". www.thewlaprize.org. Retrieved 2023-01-07.
  17. ^ Santillan, Matthew (2022-09-28). "Michael I. Jordan wins inaugural World Laureates Association Prize". EECS at UC Berkeley. Retrieved 2023-01-07.
  18. ^ 曹梓楠. "Forum honors top scientists in Shanghai". www.chinadaily.com.cn. Retrieved 2023-01-07.
  19. ^ a b c Jordan, Michael I. "Vitae" (PDF). Michael I. Jordan. Retrieved 13 November 2022.
  20. ^ Jordan, M.I.; Jacobs, R.A. (1994). "Hierarchical mixtures of experts and the EM algorithm". Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan). Vol. 2. pp. 1339–1344. CiteSeerX doi:10.1109/IJCNN.1993.716791. ISBN 978-0-7803-1421-4. S2CID 67000854. Retrieved 2015-12-19. {{cite book}}: |journal= ignored (help)
  21. ^ Editorial Board of the Kluwer Journal, Machine Learning: Resignation Letter (2001)
  22. ^ "Long Nguyen's Publications". Stat.lsa.umich.edu. Retrieved 2012-05-21.
  23. ^ "Elected AAAI Fellows". AAAI Awards. AAAI. Retrieved 13 November 2022.
  24. ^ "New IMS Fellows 2005: Congratulations to you all!" (PDF). IMS Bulletin. 34 (8): 5. 2005. Retrieved 13 November 2022.
  25. ^ "IEEE Fellows Directory — Chronological Listing". IEEE. Retrieved 13 November 2022.
  26. ^ "ASA Fellows". American Statistical Association. Retrieved 13 November 2022.
  27. ^ "Fellows". Cognitive Science Society. Retrieved 13 November 2022.
  28. ^ "ACM Names 41 Fellows from World's Leading Institutions — Association for Computing Machinery". Acm.org. Archived from the original on 2012-04-28. Retrieved 2012-05-21.
  29. ^ "Class of 2012". All SIAM Fellows. SIAM. Retrieved 13 November 2022.
  30. ^ Petrone, Sonia (2014). "ISBA Fellows" (PDF). The ISBA Bulletin. 21 (3): 5–6. Retrieved 13 November 2022.
  31. ^ "Who's the Michael Jordan of computer science? New tool ranks researchers' influence". Science | AAAS. 2016-04-19. Retrieved 2016-12-09.
  32. ^ "Artificial Intelligence—The Revolution Hasn’t Happened Yet." https://hdsr.mitpress.mit.edu/pub/wot7mkc1/release/9. Retrieved 29 November 2021
  33. ^ "Michael I. JORDAN - 2022 - WLA Prize". www.thewlaprize.org. Retrieved 2023-01-07.
  34. ^ "About - WLA Prize". www.thewlaprize.org. Retrieved 2023-01-07.